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Implements high-dimensional general linear hypothesis tests using ridge, reciprocal cubic polynomial, and user-defined analytic spectral regularizers. Provides prior-based shrinkage selection and Gaussian maximum calibration for composite tests. Implements the methods of Li, Aue and Paul (2020), "High-dimensional general linear hypothesis tests via non-linear spectral shrinkage", Bernoulli, 26(4), 2541-2571 <doi:10.3150/19-BEJ1186>.
| Version: | 0.1.0 |
| Imports: | stats |
| Published: | 2026-10-27 |
| DOI: | 10.32614/CRAN.package.ReguGLH |
| Author: | Haoran Li [aut, cre] |
| Maintainer: | Haoran Li <hzl0152 at auburn.edu> |
| Contact: | Haoran Li <haoranli1990@gmail.com> (secondary email) |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Citation: | ReguGLH citation info |
| Materials: | README, NEWS |
| CRAN checks: | ReguGLH results |
| Reference manual: | ReguGLH.html , ReguGLH.pdf |
| Package source: | ReguGLH_0.1.0.tar.gz |
| Windows binaries: | r-devel: ReguGLH_0.1.0.zip, r-release: ReguGLH_0.1.0.zip, r-oldrel: not available |
| macOS binaries: | r-release (arm64): ReguGLH_0.1.0.tgz, r-oldrel (arm64): ReguGLH_0.1.0.tgz, r-release (x86_64): ReguGLH_0.1.0.tgz, r-oldrel (x86_64): ReguGLH_0.1.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.